Lead Data Governance Analyst

Circle K Stores Inc.
Tempe, United States of America
6 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, Spanish
Experience level
Senior

Job location

Tempe, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Azure
Information Systems
Information Engineering
Data Governance
Data Infrastructure
Data Security
Metadata
Meta-Data Management
Metadata Repositories
Metadata Standards
Snowflake
Information Technology
Data Analytics
Data Management
Databricks

Job description

The Senior Data Governance & AI Enablement Lead is responsible for advancing Circle K's enterprise data governance strategy with a focus on:

  • Policy Implementation

  • Stewardship Coordination

  • AI Governance and Enablement

  • Data Product Governance

  • Data Platform Certification

  • Metadata and Catalog Oversight

  • Data Quality and Trust

  • Data Monetization Enablement

  • Compliance Support

  • Governance Adoption and Change Management

This role will partner closely with Data Product Managers, Business Product Managers, Data Stewards, Data Engineering, Analytics, Architecture, Security, Privacy, AI, and Business stakeholders to establish trusted, discoverable, reusable, and certified data assets that drive business outcomes and support responsible AI adoption.

A key responsibility will be leading governance and certification efforts across Snowflake Horizon Catalog, Databricks Unity Catalog, and Informatica, ensuring business users and AI solutions have access to trusted and governed data products.

Success in this role will be measured through increased adoption of certified data products, improved data trust, accelerated data access, enhanced AI readiness, and measurable business value generated through governed data assets.

Key Responsibilities

AI Governance & Enablement

  • Support the development and implementation of enterprise AI Data Governance frameworks, standards, and controls.

  • Partner with AI, Analytics, and Data Science teams to ensure AI solutions utilize trusted and governed data assets.

  • Support AI governance reviews, risk assessments, and approval processes.

  • Establish metadata, lineage, and data quality requirements that improve AI readiness.

  • Drive responsible AI practices aligned with regulatory, privacy, and governance requirements.

Data Products & Data Monetization

  • Support the development, certification, and governance of enterprise Data Products across Customer, Item, Site, Vendor, Finance, Loyalty, Fuel, HR, and Digital domains.

  • Partner with Data Product Managers and business stakeholders to define governance requirements and success criteria for data products.

  • Enable Data Monetization opportunities by ensuring data assets are discoverable, trusted, reusable, and scalable.

  • Support measurement of Data Product adoption, usage, business value, and operational effectiveness.

  • Identify opportunities to leverage data as a strategic asset to improve revenue, reduce costs, enhance customer experiences, and support AI innovation.

  • Develop governance processes that accelerate self-service analytics and data product consumption while maintaining appropriate controls.

Data Platform Certification

  • Establish and manage enterprise certification processes for datasets and data products.

  • Drive adoption of trusted and certified assets across Snowflake and Databricks.

  • Define certification standards including:

  • Business ownership

  • Data stewardship

  • Metadata completeness

  • Data quality thresholds

  • Lineage validation

  • Regulatory compliance

  • Security classification

  • Maintain certification workflows, scorecards, and reporting.

Metadata & Catalog Governance

  • Manage business and technical metadata standards across:

  • Informatica

  • Snowflake Horizon Catalog

  • Databricks Unity Catalog

  • Support implementation of the Enterprise "Catalog of Catalogs" strategy.

  • Drive business glossary development and stewardship.

  • Improve data discoverability through metadata enrichment and governance automation.

  • Support synchronization of metadata, classifications, glossary terms, lineage, and governance information across platforms.

Data Quality & Governance Operations

  • Partner with business and technical teams to identify Critical Data Elements (CDEs).

  • Support enterprise data quality monitoring, scorecards, issue management, and remediation processes.

  • Assist with implementation of AI-assisted data quality monitoring and governance automation capabilities.

  • Develop governance metrics and executive reporting.

Governance Adoption & Change Management

  • Lead governance enablement, training, and awareness programs.

  • Support Data Owners, Data Stewards, Data Product Owners, and Data Custodians in executing governance responsibilities.

  • Develop communications, training materials, job aids, and governance documentation.

  • Promote adoption of certified datasets, trusted data products, and governance best practices across the enterprise., * Reduced time required to discover, access, and utilize trusted data.

  • Increased business value generated through governed Data Products.

  • Enhanced AI readiness and governance compliance.

  • Increased participation from Data Owners, Data Stewards, and Data Product Owners.

  • Demonstrated support of Data Monetization opportunities through improved accessibility, quality, and governance of enterprise data assets.

  • Improved governance maturity, operational efficiency, and user satisfaction.

Why Join Circle K?

This is an opportunity to shape the future of Data Governance, AI Data Enablement, and Data Products at a global organization undergoing significant digital transformation. You will help establish trusted data foundations, enable responsible AI adoption, drive Data Product success, and unlock business value through governed and monetized data assets.

Requirements

  • 7+ years of experience in Data Governance, Data Management, Data Quality, Metadata Management, Data Products, or related disciplines.

  • Experience supporting enterprise governance programs and governance operating models.

  • Strong knowledge of:

  • Data Governance

  • Data Quality

  • Metadata Management

  • Data Cataloging

  • Master Data Management

  • Data Product Management

  • AI Governance

  • Experience working with modern cloud platforms including:

  • Snowflake

  • Databricks

  • AWS or Azure

  • Understanding of AI readiness, responsible AI practices, and governance frameworks.

  • Experience driving adoption, change management, and stakeholder engagement initiatives.

  • Strong communication and executive presentation skills.

  • Experience working in Agile delivery environments.

Preferred Qualifications

  • Experience with Informatica IDMC, Data Catalog, Data Quality, MDM, or Governance solutions.

  • Experience with Snowflake Horizon Catalog and Databricks Unity Catalog.

  • Experience implementing data certification and trusted data product programs.

  • Experience supporting Data Product operating models and Data Mesh concepts.

  • Familiarity with GDPR, CCPA, SOX, PCI, and other regulatory frameworks.

  • Experience supporting Data Monetization, customer analytics, digital products, or advanced analytics initiatives.

  • CDMP certification or similar industry certification preferred.

  • MBA or advanced degree in Information Systems, Computer Science, Data Analytics, Business, or related field preferred., In English

In Spanish

About the company

At Circle K, data is a strategic enterprise asset that powers growth, operational excellence, customer engagement, analytics, and AI innovation. As part of our Enterprise Data Governance organization, we are building modern governance capabilities that enable trusted data, certified data products, AI readiness, and scalable business value across a global enterprise.

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